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首页> 外文期刊>Journal of web engineering >Heterogeneous Identity Expression and Association Method Based on Attribute Aggregation
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Heterogeneous Identity Expression and Association Method Based on Attribute Aggregation

机译:基于属性聚合的异构特性表达式和关联方法

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摘要

Existing identity expression methods are often limited in a single security domain, and this is inadequate to meet the cross-domain access requirements of heterogeneous networks. In view of this problem, we propose an index system for the ubiquitous expression of heterogeneous identities, and introduce the concept pair matching based attribute aggregation method by combining the characteristics of heterogeneous identity alliances. The selection of concept pairs considers the original meaning of attribute characteristics, including the lexical level, i.e., class, ontology, label, description, the structural level, i.e., position, distance between nodes, and the semantic level, i.e., formal concept analysis. As for the attribute aggregation, if multiple attributes from a heterogeneous network contain the same or similar concepts, they are considered the same attribute for the user identity in a heterogeneous network. Relevant domain knowledge or heuristic knowledge will adjust the result of attribute aggregation, and the constraint relationship between conceptual structures are used to adjust and optimize the attribute aggregation set. Based on the identity attribute index system of the heterogeneous identity alliance, the identity similarity evaluation results based on each attribute are generated. When the comprehensively considered identity similarity evaluation result is higher than the empirical threshold, the heterogeneous identity alliance has different trusts for the same user. The experimental results show that our scheme has a better overall aggregation effect on identity attribute aggregation.
机译:现有身份表达式方法通常在单个安全域中受到限制,这是不充分的,以满足异构网络的跨域访问要求。鉴于这个问题,我们提出了一种用于异构身份的无处不在的表达的索引系统,并通过组合异构标识联盟的特征来引入基于基于属性聚合方法的概念对。概念对的选择考虑了属性特征的原始含义,包括词汇级别,即类,本体,标签,描述,结构级,即位置,节点之间的距离,以及语义级别,即正式概念分析。至于属性聚合,如果来自异构网络的多个属性包含相同或相似的概念,则它们被认为是异构网络中的用户身份的相同属性。相关域知识或启发式知识将调整属性聚合的结果,并且概念结构之间的约束关系用于调整和优化属性聚合集。基于异构身份联盟的身份属性索引系统,生成基于每个属性的身份相似性评估结果。当全面考虑的身份相似性评估结果高于经验阈值时,异构标识联盟对同一用户具有不同的信任。实验结果表明,我们的方案对身份属性聚集具有更好的整体聚集效果。

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